DBMS > Hive vs. TerminusDB vs. Trafodion

System Properties Comparison Hive vs. TerminusDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

Secondary database models

Document store
RDF store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

hive.apache.org

terminusdb.com

trafodion.apache.org

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

terminusdb.github.io/terminusdb/#

trafodion.apache.org/documentation.html

Developer

Apache Software Foundation

initially developed by Facebook

DataChemist Ltd.

Apache Software Foundation, originally developed by HP

Initial release

2012

2018

2014

Current release

3.1.3, April 2022

11.0.0, January 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL V3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Prolog, Rust

C++, Java

Server operating systems

All OS with a Java VM

Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
ODBC
Thrift

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
PHP
Python

JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Journaling Streams

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users, groups and roles

Role-based access control

fine grained access rights according to SQL-standard

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More resources

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